We point out some connections between applications of semidefinite programming
in control and in combinatorial optimization. In both fields semidefinite
programs arise as convex relaxations of NP-hard quadratic optimization
problems. We also show that these relaxations are readily extended to
optimization problems over bilinear matrix inequalities.